Genetic algorithm-based hysteresis modeling and identification of rotary SMA actuators

Abstract

This paper describes a new, modified generalized Preisach model for actuators that have severe dead-zone hysteresis, which is mainly observed in rotary SMA actuators. Along with the Preisach model, a new approach of hysteresis modeling and parameter identification using genetic algorithm was proposed. This modeling method achieved significant improvements in both accuracy and computation time. The proposed approach is general; therefore, it can be applied to identify any type of hysteresis. To demonstrate the efficiency of the proposed model, experimental results on hysteresis identification of Rotary SMA Actuator and performance of inverse hysteresis openloop controller are provided and compared.